Papers by Abhishek Sharma

2 papers
Interactive Post-Editing for Verbosity Controlled Translation (2022.coling-1)

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Challenge: Recent machine translation models have shown to excel with aspects of translation quality like adequacy and fluency but these models still suffer notable shortcomings like out-of-domain data, low-resource languages, rare words and longer sentences.
Approach: They propose to use human-in-loop interactive post-editing models to improve translation quality and rephrase the text with a desired style variation.
Outcome: The proposed model achieves BERTScore over state-of-the-art machine translation models while maintaining the desired token-level and verbosity preference.
Neural Conversational QA: Learning to Reason vs Exploiting Patterns (2020.emnlp-main)

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Challenge: Neural Conversational QA tasks such as ShARC require systems to answer questions based on the contents of a given passage.
Approach: They propose to modify a data-set with fewer spurious patterns to exploit them . they also propose to build a heuristic-based program to exploit spurious clues .
Outcome: The proposed program exploits spurious patterns in the ShARC dataset, compared to neural models.

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